线搜索(LS)共轭梯度法非单调算法的全局收敛性  

Global Convergence of Line Search (LS) Conjugate Gradient Algorithm with Nonmonotone Technique

作　　者：陈茜[1] 桂胜华[2] 

机构地区：[1]同济大学应用数学系,上海200092 [2]上海第二工业大学理学院,上海201029

出　　处：《上海第二工业大学学报》2007年第2期98-102,共5页Journal of Shanghai Polytechnic University

基　　金：上海市教委科研基金项目(No.05RZ12)

摘　　要：非单调线搜索技巧在非线性优化中得到成功的应用与扩展,非单调线搜索下的共轭梯度法则可以提高大规模非线性优化问题的收敛速度。对LS共轭梯度法做了某些变型,在非单调线搜索下,该方法保证每次迭带都会产生下降的方向,在较弱的条件下得到算法全局收敛性。The technique of nonmonotone line search has received many successful applications and extensions in the nonlinear optimization and the speed of convergence of conjugate gradient methods under nonmonotone line search. Change. The LS conjugate gradient method was changed in this paper, in which the technique of nonmonotone line search is used. Under mild assumption, the global convergence of the method was proved.

关 键 词：非单调线搜索 全局收敛性 修正LS算法 无约束优化 

分 类 号：O221.2[理学—运筹学与控制论]